Detection of COVID-19 from X-rays using Hybrid Deep Learning Models

Abstract In this paper, a hybrid deep learning model is proposed for the detection of coronavirus from chest X-ray images. The hybrid deep learning model is a combination of ResNet50 and MobileNet. Both ResNet50 and MobileNet are light Deep Neural Networks (DNNs) and can be used with low hardware resource-based Personal Digital Assistants (PDA) for quick detection of COVID-19 infection. The performance of the proposed hybrid model is evaluated on two publicly available COVID-19 chest X-ray datasets. Both datasets include normal, pneumonia and coronavirus infected chest X-rays. Results show that the proposed hybrid model more suitable for COVID-19 detection and achieve the highest recognition accuracy on both the datasets.